Showing 1 - 2 of 2 Research Library Publications

Quantifying the Bias of Non-linear Equating and Score Transformations

Posted: | Matthias von Davier, Brian Clauser

Essays on Contemporary Psychometrics: Pages 163-180

 

This paper shows that using non-linear functions for equating and score transformations leads to consequences that are not commensurable with classical test theory (CTT). More specifically, a well-known theorem from calculus shows that the expected value of a non-linearly transformed variable does not equal the transformed expected value of this variable.

Category:Assessment-Oriented Research, Scoring

Conditional Subscore Reporting Using Iterated Discrete Convolutions

Posted: | R.A. Feinberg, M. von Davier

Journal of Educational and Behavioral Statistics: Vol 45, Issue 5, 2020

 

This article describes a method for identifying and reporting unexpectedly high or low subscores by comparing each examinee’s observed subscore with a discrete probability distribution of subscores conditional on the examinee’s overall ability.

Category:Assessment-Oriented Research, Scoring